Summary

Dataset 1

Experiments excluded

Mask

Get figure file: figures/preliminary_dset-1_figure-mask.png

Peak coordinates

Get figure file: figures/preliminary_dset-1_figure-static.png
Get figure file: figures/preliminary_dset-1_figure-legend.png

Explorer

Meta-Analysis

Estimator

Parameters use to fit the meta-analytic estimator.

Corrector

Parameters use to fit the corrector.

Corrected meta-analytic map: z_corr-FDR_method-indep

Explorer

The following figure provides an interactive window to explore the meta-analytic map in detail.

Slice viewer

This panel shows the the corrrected meta-analytic map.

Get figure file: figures/corrector_figure-static.png

Diagnostics

Target image: z_corr-FDR_method-indep

Significant clusters

    X Y Z Peak Stat Cluster Size (mm3)
Tail Cluster ID          
Positive 1 32.00 22.00 2.00 4.77 16048
1a 40.00 24.00 2.00 4.77
1b 30.00 22.00 0.00 4.77
1c 38.00 20.00 -8.00 4.63
2 -46.00 -56.00 20.00 4.30 8112
2a -46.00 -64.00 12.00 3.74
2b -48.00 -62.00 28.00 3.16
2c -46.00 -70.00 20.00 3.16
3 0.00 -58.00 20.00 4.30 4952
3a -6.00 -58.00 26.00 3.74
3b -2.00 -58.00 34.00 3.16
3c 0.00 -60.00 14.00 3.16
4 -8.00 52.00 -4.00 4.30 12152
4a -6.00 42.00 0.00 4.01
4b -6.00 50.00 -8.00 4.01
4c -4.00 44.00 -2.00 4.01
5 -4.00 8.00 48.00 4.30 5216
5a -8.00 14.00 52.00 2.85
5b 6.00 26.00 42.00 2.85
5c -2.00 32.00 42.00 2.85
6 -36.00 18.00 -4.00 4.30 5816
6a -26.00 18.00 2.00 3.45
6b -40.00 18.00 -10.00 3.45
6c -34.00 20.00 4.00 3.16
7 58.00 -4.00 -10.00 3.74 1328
7a 58.00 2.00 -16.00 2.85
7b 58.00 -8.00 -18.00 2.54
8 54.00 -52.00 22.00 3.74 4880
8a 58.00 -40.00 20.00 3.74
8b 60.00 -48.00 20.00 3.45
8c 58.00 -36.00 20.00 3.16
9 48.00 -64.00 8.00 3.74 3576
9a 52.00 -70.00 4.00 3.45
9b 46.00 -68.00 12.00 3.16
9c 46.00 -64.00 -4.00 3.16
10 46.00 12.00 26.00 3.45 712
10a 46.00 6.00 32.00 2.20
11 26.00 -6.00 -14.00 3.45 2616
11a 18.00 -2.00 -16.00 2.85
11b 24.00 -6.00 -20.00 2.85
11c 24.00 -10.00 -12.00 2.85
12 -50.00 4.00 26.00 3.16 1760
12a -42.00 6.00 32.00 2.54
12b -40.00 -2.00 38.00 2.54
12c -50.00 2.00 30.00 2.20
13 20.00 -52.00 -12.00 2.85 976
13a 32.00 -50.00 -14.00 2.54
13b 16.00 -50.00 -12.00 2.20
13c 22.00 -54.00 -16.00 2.20
14 -46.00 -40.00 48.00 2.85 576
14a -54.00 -38.00 46.00 1.84
14b -46.00 -38.00 40.00 1.84
14c -44.00 -36.00 50.00 1.84
15 -38.00 52.00 6.00 2.85 936
15a -42.00 44.00 -2.00 2.20
15b -36.00 46.00 4.00 2.20
15c -36.00 52.00 10.00 2.20
16 56.00 2.00 -2.00 2.54 376
16a 60.00 -6.00 2.00 1.84
17 26.00 -2.00 58.00 2.54 328
18 -26.00 4.00 58.00 2.54 1104
18a -24.00 -4.00 54.00 2.20
18b -26.00 0.00 64.00 2.20
18c -30.00 -4.00 54.00 1.84
19 -28.00 -62.00 48.00 2.54 1128
19a -26.00 -70.00 38.00 2.54
19b -26.00 -62.00 46.00 2.54
19c -22.00 -70.00 38.00 2.54
20 56.00 -42.00 44.00 2.54 136
21 -46.00 34.00 20.00 2.54 96
22 -24.00 -54.00 -14.00 2.20 184
23 48.00 26.00 2.00 2.20 144
24 50.00 -42.00 48.00 2.20 88
25 50.00 22.00 8.00 2.20 88
26 -54.00 -2.00 -14.00 2.20 88
27 54.00 -56.00 -10.00 1.84 136

Label map: positive tail

Get figure file: figures/diagnostics_tail-positive_figure.png

FocusCounter

The FocusCounter analysis characterizes the relative contribution of each experiment in a meta-analysis to the resulting clusters by counting the number of peaks from each experiment that fall within each significant cluster.

The heatmap presents the relative contributions of each experiment to each cluster in the thresholded map. There is one row for each experiment, and one column for each cluster, with column names being PostiveTail/NegativeTail indicating the sign (+/-) of the cluster's statistical values. The rows and columns were re-ordered to form clusters in the heatmap.

Heatmap: positive tail

Methods

We kindly ask to report results preprocessed with this tool using the following boilerplate.

A multilevel kernel density (MKDA) meta-analysis \citep{wager2007meta} was performed was performed
with NiMARE 0.6.1 (RRID:SCR_017398; \citealt{Salo2023}), using a(n) MKDA kernel. An MKDA kernel
\citep{wager2007meta} was used to generate study-wise modeled activation maps from coordinates. In
this kernel method, each coordinate is convolved with a sphere with a radius of 10.0 and a value of
1. For voxels with overlapping spheres, the maximum value was retained. Summary statistics (OF
values) were converted to p-values using an approximate null distribution. The input dataset
included 1480 foci from 196 experiments. False discovery rate correction was performed with the
Benjamini-Hochberg procedure \citep{benjamini1995controlling}.

Bibliography

@article{Salo2023,
  doi = {10.52294/001c.87681},
  url = {https://doi.org/10.52294/001c.87681},
  year = {2023},
  volume = {3},
  pages = {1 - 32},
  author = {Taylor Salo and Tal Yarkoni and Thomas E. Nichols and Jean-Baptiste Poline and Murat Bilgel and Katherine L. Bottenhorn and Dorota Jarecka and James D. Kent and Adam Kimbler and Dylan M. Nielson and Kendra M. Oudyk and Julio A. Peraza and Alexandre Pérez and Puck C. Reeders and Julio A. Yanes and Angela R. Laird},
  title = {NiMARE: Neuroimaging Meta-Analysis Research Environment},
  journal = {Aperture Neuro}
}
@article{benjamini1995controlling,
  title={Controlling the false discovery rate: a practical and powerful approach to multiple testing},
  author={Benjamini, Yoav and Hochberg, Yosef},
  journal={Journal of the Royal statistical society: series B (Methodological)},
  volume={57},
  number={1},
  pages={289--300},
  year={1995},
  publisher={Wiley Online Library},
  url={https://doi.org/10.1111/j.2517-6161.1995.tb02031.x},
  doi={10.1111/j.2517-6161.1995.tb02031.x}
}
@article{wager2007meta,
  title={Meta-analysis of functional neuroimaging data: current and future directions},
  author={Wager, Tor D and Lindquist, Martin and Kaplan, Lauren},
  journal={Social cognitive and affective neuroscience},
  volume={2},
  number={2},
  pages={150--158},
  year={2007},
  publisher={Oxford University Press},
  url={https://doi.org/10.1093/scan/nsm015},
  doi={10.1093/scan/nsm015}
}